A non-empirical model for gas transfer through circular nanopores in unconventional gas reservoirs

It is difficult to predict the flow performance in the nanopore networks since traditional assumptions of Navier–Stokes equation break down. At present, lots of attempts have been employed to address the proposition. In this work, the advantages and disadvantages of previous analytical models are seriously analyzed. The first type is modifying a mature equation which is proposed for a specified flow regime and adapted to wider application scope. Thus, the first-type models inevitably require empirical coefficients. The second type is weight superposition based on two different flow mechanisms, which is considered as the reasonable establishment method for universal non-empirical gas-transport model. Subsequently, in terms of slip flow and Knudsen diffusion, the novel gas-transport model is established in this work. Notably, the weight factors of slip flow and Knudsen diffusion are determined through Wu’s model and Knudsen’s model respectively, with the capacity to capture key transport mechanism through nanopores. Capturing gas flow physics at nanoscale allows the proposed model free of any empirical coefficients, which is also the main distinction between our work and previous research. Reliability of proposed model is verified by published molecular simulation results as well. Furthermore, a novel permeability model for coal/shale matrix is developed based on the non-empirical gas-transport model. Results show that (a) nanoconfined gas-transport capacity will be strengthened with the decline of pressure and the decrease in the pressure is supportive for the increasing amplitude; (b) the greater pore size the nanopores is, the stronger the transport capacity the nanotube is; (c) after field application with an actual well in Fuling shale gas field, China, it is demonstrated that numerical simulation coupled with the proposed permeability model can achieve better historical match with the actual production performance. The investigation will contribute to the understanding of nanoconfined gas flow behavior and lay the theoretical foundation for next-generation numerical simulation of unconventional gas reservoirs.

Simulated Annealing Algorithm-Based Inversion Model To Interpret Flow Rate Profiles and Fracture Parameters for Horizontal Wells in Unconventional Gas Reservoirs

Summary With the increasing application of distributed temperature sensing (DTS) in downhole monitoring for multifractured horizontal wells (MFHWs), well performance interpretation by inversing DTS data has become a popular topic around the world. However, because of the lack of efficient inversion models, great challenges still exist in interpreting flow rate profiles and fracture parameters for MFHWs in unconventional gas reservoirs from DTS data. In this paper, a robust inversion system is developed to interpret flow rate profiles and fracture parameters for MFHWs in unconventional gas reservoirs by inversion of DTS data. A temperature prediction model serves as a forward model to simulate the temperature behaviors of MFHWs. A new inversion model based on a simulated annealing (SA) algorithm is proposed to find inversion solutions to flow rate profiles and fracture parameters. The simulated results of temperature behaviors indicate that the temperature profile of each MFHW is irregularly serrated, and the temperature drop in each serration is positively correlated with the inflow rate and fracture half-length. These results provide an excellent method to identify and locate effective hydraulic fractures for field MFHWs. Because of the far more significant influence of fracture half-length than conductivity on a temperature profile, fracture half-length was chosen as the inversion target parameter when performing the inversion of DTS data for MFHWs. Then a synthetic inversion task was accomplished using the SA algorithm-based inversion system, and it took only 110 iterations to reach the target inversion accuracy (10−6 level). Real-time inversion error distributions indicate that this novel inversion system shows great advantages in computational efficiency. Finally, a field application in a shale gas reservoir is presented to validate the reliability of the new inversion model. Based on accurate identification of effective fractures from DTS profiles, satisfactory inversion solutions (the maximum temperature deviation of less than 0.03 K) are obtained. The absolute error of the inversed gas production rate is less than 4 m3/d. The SA algorithm-based inversion system proves reliable to interpret flow rate profiles and fracture parameters, which is a great help to postfracturing evaluation and productivity improvement for MFHWs in unconventional gas reservoirs.